The Weekly Index #5 — GPT Actions in 2026: 1,818 Indexed, All Scored 26–29. Here Is the Honest Assessment.

Issue #5 of The Weekly Index. This week: an honest, data-backed look at the GPT Actions ecosystem in 2026 — a category we have 1,818 tools indexed in, and one that tells an interesting story about where the market went.

📊 This Week's Numbers

1,818 GPT Actions in our index (across awesome_gpts, awesome_chatgpt_plugins, awesome_gpt_store sources)
26–29 out of 100 — the scoring range for every GPT Action in our index
100% have maintenance_status "unknown" in our database — a telling data point
This week's research assistant stack guide is the most practical thing we have published. Six tools, one config block.

🔦 The Honest Assessment: Why GPT Actions Score So Low

1,818 GPT Actions in our index all scoring 26–29 out of 100 is not a coincidence or a model artifact. It reflects three real structural issues:

1. Maintenance Is Unverifiable

GPT Actions live inside the ChatGPT interface. There is no public repository to commit to, no npm package with a version history, no GitHub release page. We cannot verify when a GPT Action was last updated, whether its underlying API is still live, or whether the creator is still maintaining it. This kills our maintenance_score.

2. Security Cannot Be Audited

The code that powers a GPT Action is not public (unless the creator open-sourced it separately). We cannot audit permissions, network calls, or data handling. This hurts the security_score significantly. For comparison: 37.2% of MCP servers in our index earn a 5/5 security score. Among GPT Actions: 0%.

3. Many Are Abandoned Without Indication

The "awesome-gpts" lists were assembled in 2023–2024 during peak GPT Store enthusiasm. An unknown but likely significant fraction of these Actions point to APIs that no longer exist, or have configurations that no longer work. We have no way to programmatically test this at scale.

📈 What Still Works in the GPT Actions Ecosystem

This is not a "GPT Actions are dead" take. There are real workflows where they still make sense:

Internal company GPTs — a custom GPT with Actions connected to your internal APIs (Jira, Notion, Salesforce) is a legitimate use case. The verification problem does not apply when you control the Action.
Stable third-party integrations — Actions built by companies like Kayak, Wolfram Alpha, or Expedia that have public APIs and dedicated support teams maintain reasonable uptime.
ChatGPT-specific workflows — if your team runs on ChatGPT rather than Claude or Cursor, Actions are the native integration format. MCP servers are not relevant here.

🆕 The 5 GPT Actions That Still Earn Their Place

From our 1,818 indexed, these have the strongest signals of ongoing relevance:

LLM Research Storm — Research synthesis tool with strong community engagement
API Docs — OpenAI API documentation assistant, maintained by OpenAI directly
GPT Creator Workshop — Useful for teams building their own GPTs internally
EmbeddedGPT — Embedded systems knowledge, niche but specific use case
FixGPT — Troubleshooting GPT — quirky but functionally useful for new ChatGPT users

⚙️ Use Case Corner: When to Use GPT Actions vs MCP Servers

Situation	Use
Your team uses ChatGPT, not Claude	GPT Actions
You need a verified, auditable integration	MCP Server
You are building internal tooling	Either (MCP preferred for auditability)
You need cross-platform (Claude + Cursor + ChatGPT)	MCP Server
You found a specific GPT that does exactly what you need	GPT Action (verify it still works first)

👥 Community Picks

MindsDB MCP — 38.5k GitHub stars, 97/100. AI-powered database queries. For teams wanting ML predictions directly from database queries.
screenpipe — 17k stars, 94/100. Local AI screen recording and context capture. Privacy-first alternative to cloud-based activity trackers.

Next week: our final editor's picks issue — the 10 best tools across all categories. See you Thursday. Past issues